• 제목/요약/키워드: Particle Trajectory

검색결과 172건 처리시간 0.019초

습식분류층 석탄가스화기 수치해석 및 실험적 연구 (Numerical and Experimental Study on the Coal Reaction in an Entrained Flow Gasifier)

  • 김혜숙;최승희;황민정;송우영;신미수;장동순;윤상준;최영찬;이재구
    • 대한환경공학회지
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    • 제32권2호
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    • pp.165-174
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    • 2010
  • 석탄 가스화 반응을 모델링하여 습식분류층 석탄 가스화기의 반응특성에 대한 수치해석적 연구를 수행하였다. 본 연구의 목적은 신뢰성 있는 수치해석기술을 이용하여 가스화 장치의 기본설계와 더불어 최적 운전조건의 설정에 있다. 석탄 가스화 반응은 복사가 관여하는 고체와 기체의 이상 난류반응으로서 수증기 증발로부터 휘발화, 촤와 가스의 반응 등 일련의 연소반응의 구조를 가진다. 본 연구에서는 실험과 수치해석적인 방법을 병행하여 연구를 수행하였으며 한국에너지기술연구원에 설치된 1톤 규모의 실험용 가스화기를 대상으로 하였다. 본 연구에서는 기본적으로 상용프로그램을 사용하였으며 석탄 가스화 반응해석에 필요한 여러 서브루틴을 개발하여 해석하였다. 세부 반응 서브루틴의 난류반응은 기본적으로 에디붕괴모델에서 화학적 반응속도의 개념을 조화평균의 형태로 사용하였다. 그리고 석탄입자궤적은 라그란지안 접근방식을 선택하였으며 입자의 궤적 계산에서 저항력에 나타나는 난류비선형적인 문제에 대한 모델도 고려하였다. 이와 같이 개발된 프로그램은 실험에서 얻어진 가스농도와 온도분포 그리고 냉가스 효율 등의 자료들과 비교하여 성능을 일차적으로 검토하였다. 석탄의 입자크기분포, 석탄 슬러리 농도, 그리고 가스화기의 형상변화는 가스화 성능에 직접적으로 영향을 주며 이를 합성가스 생성량과 냉가스 효율을 통해 비교 검토하였다. 본 연구 결과가 비록 물리적으로 타당하고 변수연구의 일관성을 보여주나 기류층 석탄가스화 반응장치의 복잡성을 고려하여 볼 때 보다 많은 실험결과에 대한 정교한 모델검증 노력이 신뢰성 있는 프로그램의 완성에 필요할 것으로 판단된다.

대기오염집중측정소별 2013~2015년 사이의 PM2.5 화학적 특성 차이 및 유발인자 조사 (Difference in Chemical Composition of PM2.5 and Investigation of its Causing Factors between 2013 and 2015 in Air Pollution Intensive Monitoring Stations)

  • 유근혜;박승식;김영성;신혜정;임철수;반수진;유정아;강현정;서영교;강경식;조미라;정선아;이민희;황태경;강병철;김효선
    • 한국대기환경학회지
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    • 제34권1호
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    • pp.16-37
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    • 2018
  • In this study, difference in chemical composition of $PM_{2.5}$ observed between the year 2013 and 2015 at six air quality intensive monitoring stations (Bangryenogdo (BR), Seoul (SL), Daejeon (DJ), Gwangju (GJ), Ulsan (US), and Jeju (JJ)) was investigated and the possible factors causing their difference were also discussed. $PM_{2.5}$, organic and elemental carbon (OC and EC), and water-soluble ionic species concentrations were observed on a hourly basis in the six stations. The difference in chemical composition by regions was examined based on emissions of gaseous criteria pollutants (CO, $SO_2$, and $NO_2$), meteorological parameters (wind speed, temperature, and relative humidity), and origins and transport pathways of air masses. For the years 2013 and 2014, annual average $PM_{2.5}$ was in the order of SL ($${\sim_=}DJ$$)>GJ>BR>US>JJ, but the highest concentration in 2015 was found at DJ, following by GJ ($${\sim_=}SJ$$)>BR>US>JJ. Similar patterns were found in $SO{_4}^{2-}$, $NO_3{^-}$, and $NH_4{^+}$. Lower $PM_{2.5}$ at SL than at DJ and GJ was resulted from low concentrations of secondary ionic species. Annual average concentrations of OC and EC by regions had no big difference among the years, but their patterns were distinct from the $PM_{2.5}$, $SO{_4}^{2-}$, $NO_3{^-}$, and $NH_4{^+}$ concentrations by regions. 4-day air mass backward trajectory calculations indicated that in the event of daily average $PM_{2.5}$ exceeding the monthly average values, >70% of the air masses reaching the all stations were coming from northeastern Chinese polluted regions, indicating the long-range transportation (LTP) was an important contributor to $PM_{2.5}$ and its chemical composition at the stations. Lower concentrations of secondary ionic species and $PM_{2.5}$ at SL in 2015 than those at DJ and GJ sites were due to the decrease in impact by LTP from polluted Chinese regions, rather than the difference in local emissions of criteria gas pollutants ($SO_2$, $NO_2$, and $NH_3$) among the SL, DJ, and GJ sites. The difference in annual average $SO{_4}^{2-}$ by regions was resulted from combination of the difference in local $SO_2$ emissions and chemical conversion of $SO_2$ to $SO{_4}^{2-}$, and LTP from China. However, the $SO{_4}^{2-}$ at the sites were more influenced by LTP than the formation by chemical transformation of locally emitted $SO_2$. The $NO_3{^-}$ increase was closely associated with the increase in local emissions of nitrogen oxides at four urban sites except for the BR and JJ, as well as the LTP with a small contribution. Among the meterological parameters (wind speed, temperature, and relative humidity), the ambient temperature was most important factor to control the variation of $PM_{2.5}$ and its major chemical components concentrations. In other words, as the average temperature increases, the $PM_{2.5}$, OC, EC, and $NO_3{^-}$ concentrations showed a decreasing tendency, especially with a prominent feature in $NO_3{^-}$. Results from a case study that examined the $PM_{2.5}$ and its major chemical data observed between February 19 and March 2, 2014 at the all stations suggest that ambient $SO{_4}^{2-}$ and $NO_3{^-}$ concentrations are not necessarily proportional to the concentrations of their precursor emissions because the rates at which they form and their gas/particle partitioning may be controlled by factors (e.g., long range transportation) other than the concentration of the precursor gases.